Overview

Dataset statistics

Number of variables17
Number of observations118080
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.3 MiB
Average record size in memory136.0 B

Variable types

Categorical1
Numeric16

Alerts

Timestamp has a high cardinality: 118080 distinct valuesHigh cardinality
ActivePower is highly overall correlated with BearingShaftTemperature and 8 other fieldsHigh correlation
AmbientTemperatue is highly overall correlated with MainBoxTemperatureHigh correlation
BearingShaftTemperature is highly overall correlated with ActivePower and 8 other fieldsHigh correlation
GearboxBearingTemperature is highly overall correlated with ActivePower and 8 other fieldsHigh correlation
GearboxOilTemperature is highly overall correlated with ActivePower and 8 other fieldsHigh correlation
GeneratorRPM is highly overall correlated with ActivePower and 8 other fieldsHigh correlation
GeneratorWinding1Temperature is highly overall correlated with ActivePower and 8 other fieldsHigh correlation
GeneratorWinding2Temperature is highly overall correlated with ActivePower and 8 other fieldsHigh correlation
HubTemperature is highly overall correlated with BearingShaftTemperature and 1 other fieldsHigh correlation
MainBoxTemperature is highly overall correlated with AmbientTemperatue and 1 other fieldsHigh correlation
NacellePosition is highly overall correlated with WindDirectionHigh correlation
ReactivePower is highly overall correlated with ActivePower and 7 other fieldsHigh correlation
RotorRPM is highly overall correlated with ActivePower and 8 other fieldsHigh correlation
WindDirection is highly overall correlated with NacellePositionHigh correlation
WindSpeed is highly overall correlated with ActivePower and 8 other fieldsHigh correlation
TurbineStatus is highly skewed (γ1 = 243.3925405)Skewed
Timestamp is uniformly distributedUniform
Timestamp has unique valuesUnique
RotorRPM has 2809 (2.4%) zerosZeros

Reproduction

Analysis started2024-02-06 05:34:07.053857
Analysis finished2024-02-06 05:34:38.734219
Duration31.68 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

Timestamp
Categorical

HIGH CARDINALITY  UNIFORM  UNIQUE 

Distinct118080
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size922.6 KiB
2018-01-01 00:00:00+00:00
 
1
2019-07-01 17:40:00+00:00
 
1
2019-07-01 17:20:00+00:00
 
1
2019-07-01 17:10:00+00:00
 
1
2019-07-01 17:00:00+00:00
 
1
Other values (118075)
118075 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2952000
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118080 ?
Unique (%)100.0%

Sample

1st row2018-01-01 00:00:00+00:00
2nd row2018-01-01 00:10:00+00:00
3rd row2018-01-01 00:20:00+00:00
4th row2018-01-01 00:30:00+00:00
5th row2018-01-01 00:40:00+00:00

Common Values

ValueCountFrequency (%)
2018-01-01 00:00:00+00:00 1
 
< 0.1%
2019-07-01 17:40:00+00:00 1
 
< 0.1%
2019-07-01 17:20:00+00:00 1
 
< 0.1%
2019-07-01 17:10:00+00:00 1
 
< 0.1%
2019-07-01 17:00:00+00:00 1
 
< 0.1%
2019-07-01 16:50:00+00:00 1
 
< 0.1%
2019-07-01 16:40:00+00:00 1
 
< 0.1%
2019-07-01 16:30:00+00:00 1
 
< 0.1%
2019-07-01 16:20:00+00:00 1
 
< 0.1%
2019-07-01 16:10:00+00:00 1
 
< 0.1%
Other values (118070) 118070
> 99.9%

Length

2024-02-05T23:34:38.792480image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02:40:00+00:00 820
 
0.3%
09:20:00+00:00 820
 
0.3%
12:10:00+00:00 820
 
0.3%
12:00:00+00:00 820
 
0.3%
11:50:00+00:00 820
 
0.3%
11:40:00+00:00 820
 
0.3%
11:20:00+00:00 820
 
0.3%
11:10:00+00:00 820
 
0.3%
11:00:00+00:00 820
 
0.3%
10:50:00+00:00 820
 
0.3%
Other values (954) 227960
96.5%

Most occurring characters

ValueCountFrequency (%)
0 1187976
40.2%
: 354240
 
12.0%
1 289992
 
9.8%
2 256584
 
8.7%
- 236160
 
8.0%
118080
 
4.0%
+ 118080
 
4.0%
8 82992
 
2.8%
9 82416
 
2.8%
3 64968
 
2.2%
Other values (4) 160512
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2125440
72.0%
Other Punctuation 354240
 
12.0%
Dash Punctuation 236160
 
8.0%
Space Separator 118080
 
4.0%
Math Symbol 118080
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1187976
55.9%
1 289992
 
13.6%
2 256584
 
12.1%
8 82992
 
3.9%
9 82416
 
3.9%
3 64968
 
3.1%
5 50112
 
2.4%
4 49824
 
2.3%
7 30432
 
1.4%
6 30144
 
1.4%
Other Punctuation
ValueCountFrequency (%)
: 354240
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 236160
100.0%
Space Separator
ValueCountFrequency (%)
118080
100.0%
Math Symbol
ValueCountFrequency (%)
+ 118080
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2952000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1187976
40.2%
: 354240
 
12.0%
1 289992
 
9.8%
2 256584
 
8.7%
- 236160
 
8.0%
118080
 
4.0%
+ 118080
 
4.0%
8 82992
 
2.8%
9 82416
 
2.8%
3 64968
 
2.2%
Other values (4) 160512
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2952000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1187976
40.2%
: 354240
 
12.0%
1 289992
 
9.8%
2 256584
 
8.7%
- 236160
 
8.0%
118080
 
4.0%
+ 118080
 
4.0%
8 82992
 
2.8%
9 82416
 
2.8%
3 64968
 
2.2%
Other values (4) 160512
 
5.4%

ActivePower
Real number (ℝ)

Distinct94085
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean619.10981
Minimum-38.524659
Maximum1779.0324
Zeros594
Zeros (%)0.5%
Negative15644
Negative (%)13.2%
Memory size922.6 KiB
2024-02-05T23:34:38.888117image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum-38.524659
5-th percentile-6.1379592
Q1149.53115
median619.10981
Q3839.50864
95-th percentile1719.1468
Maximum1779.0324
Range1817.5571
Interquartile range (IQR)689.97749

Descriptive statistics

Standard deviation547.56778
Coefficient of variation (CV)0.88444372
Kurtosis-0.43662303
Mean619.10981
Median Absolute Deviation (MAD)408.51103
Skewness0.79234386
Sum73104486
Variance299830.47
MonotonicityNot monotonic
2024-02-05T23:34:38.991106image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
619.1098054 23330
 
19.8%
0 594
 
0.5%
1730.6644 44
 
< 0.1%
-0.0003023227 8
 
< 0.1%
1575.5742 5
 
< 0.1%
-4.5095987 3
 
< 0.1%
1737.2281 3
 
< 0.1%
653.9309 3
 
< 0.1%
0.00043881143 3
 
< 0.1%
1720.429185 2
 
< 0.1%
Other values (94075) 94085
79.7%
ValueCountFrequency (%)
-38.52465939 1
< 0.1%
-38.31229862 1
< 0.1%
-29.61263391 1
< 0.1%
-22.1754245 1
< 0.1%
-19.5226848 1
< 0.1%
-15.5358763 1
< 0.1%
-15.099586 1
< 0.1%
-14.61247716 1
< 0.1%
-14.59247 1
< 0.1%
-13.87283633 1
< 0.1%
ValueCountFrequency (%)
1779.032433 1
< 0.1%
1768.1444 1
< 0.1%
1767.2888 1
< 0.1%
1757.2687 1
< 0.1%
1756.9816 1
< 0.1%
1749.25321 1
< 0.1%
1749.1084 1
< 0.1%
1748.4562 1
< 0.1%
1747.7269 1
< 0.1%
1746.1604 1
< 0.1%

AmbientTemperatue
Real number (ℝ)

Distinct93678
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.774654
Minimum0
Maximum42.405597
Zeros16
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:39.098903image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile22.530926
Q126.345902
median28.774654
Q330.719714
95-th percentile36.27812
Maximum42.405597
Range42.405597
Interquartile range (IQR)4.3738121

Descriptive statistics

Standard deviation3.8944719
Coefficient of variation (CV)0.13534383
Kurtosis0.7603081
Mean28.774654
Median Absolute Deviation (MAD)2.2195036
Skewness0.39508418
Sum3397711.2
Variance15.166911
MonotonicityNot monotonic
2024-02-05T23:34:39.198701image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28.77465406 24263
 
20.5%
28.844826 44
 
< 0.1%
27.792393 25
 
< 0.1%
0 16
 
< 0.1%
32.6452 9
 
< 0.1%
27.792393 8
 
< 0.1%
37.102978 7
 
< 0.1%
22.40376 6
 
< 0.1%
29.266325 5
 
< 0.1%
35.003857 3
 
< 0.1%
Other values (93668) 93694
79.3%
ValueCountFrequency (%)
0 16
< 0.1%
3.030066906 × 10-201
 
< 0.1%
11.13068395 1
 
< 0.1%
16.1116675 1
 
< 0.1%
18.1019715 1
 
< 0.1%
18.227419 1
 
< 0.1%
18.61710611 1
 
< 0.1%
18.71038822 1
 
< 0.1%
18.71183878 1
 
< 0.1%
18.7926749 1
 
< 0.1%
ValueCountFrequency (%)
42.4055965 1
< 0.1%
42.0209375 1
< 0.1%
42.00404011 1
< 0.1%
41.9483075 1
< 0.1%
41.92922722 1
< 0.1%
41.8949063 1
< 0.1%
41.8373459 1
< 0.1%
41.8097136 1
< 0.1%
41.78824589 1
< 0.1%
41.7411471 1
< 0.1%

BearingShaftTemperature
Real number (ℝ)

Distinct62287
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.010189
Minimum0
Maximum55.088655
Zeros225
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:39.327210image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37.503213
Q142.506199
median43.010189
Q343.299226
95-th percentile49.791328
Maximum55.088655
Range55.088655
Interquartile range (IQR)0.7930271

Descriptive statistics

Standard deviation4.0349551
Coefficient of variation (CV)0.093813935
Kurtosis25.873183
Mean43.010189
Median Absolute Deviation (MAD)0.39016936
Skewness-2.6209863
Sum5078643.1
Variance16.280862
MonotonicityNot monotonic
2024-02-05T23:34:39.431324image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43.01018906 55562
47.1%
0 225
 
0.2%
43.509945 3
 
< 0.1%
50.526719 2
 
< 0.1%
40.17997 2
 
< 0.1%
50.352311 2
 
< 0.1%
48.221169 2
 
< 0.1%
42.09256887 2
 
< 0.1%
44.817422 2
 
< 0.1%
40.57874 1
 
< 0.1%
Other values (62277) 62277
52.7%
ValueCountFrequency (%)
0 225
0.2%
13.51817567 1
 
< 0.1%
13.688085 1
 
< 0.1%
15.31223667 1
 
< 0.1%
16.119878 1
 
< 0.1%
16.805773 1
 
< 0.1%
17.263845 1
 
< 0.1%
18.43944 1
 
< 0.1%
18.901865 1
 
< 0.1%
19.473595 1
 
< 0.1%
ValueCountFrequency (%)
55.088655 1
< 0.1%
55.065134 1
< 0.1%
55.015868 1
< 0.1%
55.0057808 1
< 0.1%
54.9823555 1
< 0.1%
54.941518 1
< 0.1%
54.9390186 1
< 0.1%
54.9277441 1
< 0.1%
54.91379785 1
< 0.1%
54.8954128 1
< 0.1%

GearboxBearingTemperature
Real number (ℝ)

Distinct62314
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.23417
Minimum0
Maximum82.237932
Zeros226
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:39.547650image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile51.413712
Q164.165676
median64.23417
Q365.457586
95-th percentile78.621308
Maximum82.237932
Range82.237932
Interquartile range (IQR)1.2919099

Descriptive statistics

Standard deviation7.6091523
Coefficient of variation (CV)0.11845957
Kurtosis11.503565
Mean64.23417
Median Absolute Deviation (MAD)0.67584715
Skewness-1.5322995
Sum7584770.8
Variance57.899198
MonotonicityNot monotonic
2024-02-05T23:34:39.643117image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64.23417012 55540
47.0%
0 226
 
0.2%
67.55545 3
 
< 0.1%
59.57813475 1
 
< 0.1%
56.47278375 1
 
< 0.1%
58.18471157 1
 
< 0.1%
58.49054888 1
 
< 0.1%
58.45084287 1
 
< 0.1%
59.46783055 1
 
< 0.1%
59.58528975 1
 
< 0.1%
Other values (62304) 62304
52.8%
ValueCountFrequency (%)
0 226
0.2%
18.44888433 1
 
< 0.1%
20.80210867 1
 
< 0.1%
21.93258167 1
 
< 0.1%
23.00795 1
 
< 0.1%
23.89555 1
 
< 0.1%
23.918848 1
 
< 0.1%
24.04009 1
 
< 0.1%
25.15475875 1
 
< 0.1%
25.501198 1
 
< 0.1%
ValueCountFrequency (%)
82.237932 1
< 0.1%
82.2199136 1
< 0.1%
82.2035 1
< 0.1%
82.1906372 1
< 0.1%
82.143782 1
< 0.1%
82.1366646 1
< 0.1%
82.1098775 1
< 0.1%
82.1026621 1
< 0.1%
82.0936836 1
< 0.1%
82.0888711 1
< 0.1%

GearboxOilTemperature
Real number (ℝ)

Distinct62413
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.561217
Minimum0
Maximum70.764581
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:39.747451image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile50.333175
Q156.870556
median57.561217
Q357.561217
95-th percentile66.982323
Maximum70.764581
Range70.764581
Interquartile range (IQR)0.69066148

Descriptive statistics

Standard deviation4.5985332
Coefficient of variation (CV)0.079889436
Kurtosis8.0129401
Mean57.561217
Median Absolute Deviation (MAD)0.31837033
Skewness-0.86587615
Sum6796828.5
Variance21.146508
MonotonicityNot monotonic
2024-02-05T23:34:39.854570image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57.56121733 55642
47.1%
53.83944 7
 
< 0.1%
49.841103 3
 
< 0.1%
57.242847 3
 
< 0.1%
0 3
 
< 0.1%
58.44239 2
 
< 0.1%
59.118063 2
 
< 0.1%
55.309996 2
 
< 0.1%
52.35127 2
 
< 0.1%
61.8030382 2
 
< 0.1%
Other values (62403) 62412
52.9%
ValueCountFrequency (%)
0 3
< 0.1%
26.79651467 1
 
< 0.1%
26.799627 1
 
< 0.1%
26.8113748 1
 
< 0.1%
26.8187311 1
 
< 0.1%
26.82125144 1
 
< 0.1%
26.83231133 1
 
< 0.1%
26.83423089 1
 
< 0.1%
26.841705 1
 
< 0.1%
26.8448739 1
 
< 0.1%
ValueCountFrequency (%)
70.76458113 1
< 0.1%
70.7387834 1
< 0.1%
70.726373 1
< 0.1%
70.7131655 1
< 0.1%
70.7074472 1
< 0.1%
70.7047985 1
< 0.1%
70.6811602 1
< 0.1%
70.6800354 1
< 0.1%
70.66814578 1
< 0.1%
70.6579964 1
< 0.1%

GeneratorRPM
Real number (ℝ)

Distinct61075
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1102.0263
Minimum0
Maximum1809.9417
Zeros1037
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:39.980901image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile83.949169
Q11094.849
median1102.0263
Q31156.2887
95-th percentile1750.076
Maximum1809.9417
Range1809.9417
Interquartile range (IQR)61.439692

Descriptive statistics

Standard deviation383.55115
Coefficient of variation (CV)0.34804175
Kurtosis2.2158017
Mean1102.0263
Median Absolute Deviation (MAD)28.313314
Skewness-1.0874451
Sum1.3012726 × 108
Variance147111.49
MonotonicityNot monotonic
2024-02-05T23:34:40.075181image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1102.026269 55785
47.2%
0 1037
 
0.9%
1029.9807 3
 
< 0.1%
1290.1729 3
 
< 0.1%
1030.0546 3
 
< 0.1%
1029.96825 3
 
< 0.1%
1030.044 3
 
< 0.1%
1029.9868 3
 
< 0.1%
1030.0973 3
 
< 0.1%
1030.0489 2
 
< 0.1%
Other values (61065) 61235
51.9%
ValueCountFrequency (%)
0 1037
0.9%
0.3403373 1
 
< 0.1%
0.347509225 1
 
< 0.1%
0.3732631444 1
 
< 0.1%
0.3749087778 1
 
< 0.1%
0.3769242091 1
 
< 0.1%
0.3835448 1
 
< 0.1%
0.3925768 1
 
< 0.1%
0.3975889111 1
 
< 0.1%
0.4162656923 1
 
< 0.1%
ValueCountFrequency (%)
1809.9417 1
< 0.1%
1793.65715 1
< 0.1%
1785.7526 1
< 0.1%
1781.184 1
< 0.1%
1779.9696 1
< 0.1%
1777.52295 1
< 0.1%
1776.1821 1
< 0.1%
1775.732767 1
< 0.1%
1773.95117 1
< 0.1%
1773.6787 1
< 0.1%
Distinct62407
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.460403
Minimum0
Maximum126.77303
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:40.185024image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile48.978679
Q164.571718
median72.460403
Q372.460403
95-th percentile112.85608
Maximum126.77303
Range126.77303
Interquartile range (IQR)7.8886852

Descriptive statistics

Standard deviation16.452534
Coefficient of variation (CV)0.22705551
Kurtosis1.7988187
Mean72.460403
Median Absolute Deviation (MAD)1.84223
Skewness1.0315191
Sum8556124.4
Variance270.68586
MonotonicityNot monotonic
2024-02-05T23:34:40.295804image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72.46040299 55653
47.1%
62.229546 7
 
< 0.1%
0 5
 
< 0.1%
50.16808 3
 
< 0.1%
67.04963 3
 
< 0.1%
114.848114 2
 
< 0.1%
66.437164 2
 
< 0.1%
68.416435 2
 
< 0.1%
90.815475 2
 
< 0.1%
53.27334 2
 
< 0.1%
Other values (62397) 62399
52.8%
ValueCountFrequency (%)
0 5
< 0.1%
27.1780991 1
 
< 0.1%
27.17839578 1
 
< 0.1%
27.20894567 1
 
< 0.1%
27.2155078 1
 
< 0.1%
27.24492711 1
 
< 0.1%
27.28234022 1
 
< 0.1%
27.283243 1
 
< 0.1%
27.3229627 1
 
< 0.1%
27.3632903 1
 
< 0.1%
ValueCountFrequency (%)
126.7730308 1
< 0.1%
126.695327 1
< 0.1%
126.6502432 1
< 0.1%
126.6023713 1
< 0.1%
126.5623484 1
< 0.1%
126.556144 1
< 0.1%
126.5228585 1
< 0.1%
126.5223498 1
< 0.1%
126.5003853 1
< 0.1%
126.4818589 1
< 0.1%
Distinct62425
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.826659
Minimum0
Maximum126.04302
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:40.415844image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile48.460443
Q163.768833
median71.826659
Q371.826659
95-th percentile112.29898
Maximum126.04302
Range126.04302
Interquartile range (IQR)8.0578264

Descriptive statistics

Standard deviation16.471989
Coefficient of variation (CV)0.22932974
Kurtosis1.7791113
Mean71.826659
Median Absolute Deviation (MAD)1.8987506
Skewness1.0434466
Sum8481291.9
Variance271.32642
MonotonicityNot monotonic
2024-02-05T23:34:40.531027image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.82665932 55631
47.1%
61.686092 7
 
< 0.1%
0 5
 
< 0.1%
49.75333 3
 
< 0.1%
66.4111 3
 
< 0.1%
51.022415 2
 
< 0.1%
61.89688 2
 
< 0.1%
65.577225 2
 
< 0.1%
114.21849 2
 
< 0.1%
68.0335346 2
 
< 0.1%
Other values (62415) 62421
52.9%
ValueCountFrequency (%)
0 5
< 0.1%
26.9411411 1
 
< 0.1%
26.96148544 1
 
< 0.1%
26.99946544 1
 
< 0.1%
27.03277189 1
 
< 0.1%
27.04038022 1
 
< 0.1%
27.0749868 1
 
< 0.1%
27.1180875 1
 
< 0.1%
27.15934869 1
 
< 0.1%
27.20134823 1
 
< 0.1%
ValueCountFrequency (%)
126.0430176 1
< 0.1%
125.9687988 1
< 0.1%
125.9227522 1
< 0.1%
125.8888851 1
< 0.1%
125.8427976 1
< 0.1%
125.8374666 1
< 0.1%
125.7856394 1
< 0.1%
125.7829339 1
< 0.1%
125.7711597 1
< 0.1%
125.7508729 1
< 0.1%

HubTemperature
Real number (ℝ)

Distinct38117
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.897978
Minimum0
Maximum47.996185
Zeros305
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:40.640876image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile31.002037
Q136.897978
median36.897978
Q337.327458
95-th percentile43.003815
Maximum47.996185
Range47.996185
Interquartile range (IQR)0.42948071

Descriptive statistics

Standard deviation3.7648271
Coefficient of variation (CV)0.10203343
Kurtosis24.123305
Mean36.897978
Median Absolute Deviation (MAD)0.10583743
Skewness-2.5405902
Sum4356913.2
Variance14.173923
MonotonicityNot monotonic
2024-02-05T23:34:40.751490image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.89797757 55674
47.1%
39.996185 1085
 
0.9%
40.003815 963
 
0.8%
41.996185 932
 
0.8%
43.996185 850
 
0.7%
42.003815 750
 
0.6%
37.996185 682
 
0.6%
36.996185 652
 
0.6%
38.003815 639
 
0.5%
34.996185 544
 
0.5%
Other values (38107) 55309
46.8%
ValueCountFrequency (%)
0 305
0.3%
3.0937654 1
 
< 0.1%
4.0806705 1
 
< 0.1%
5.6548783 1
 
< 0.1%
7.4043364 1
 
< 0.1%
7.75139275 1
 
< 0.1%
8.219612111 1
 
< 0.1%
10.24810462 1
 
< 0.1%
10.50502857 1
 
< 0.1%
12.67044333 1
 
< 0.1%
ValueCountFrequency (%)
47.996185 2
 
< 0.1%
47.996185 22
< 0.1%
47.9961751 1
 
< 0.1%
47.9959882 1
 
< 0.1%
47.9959267 1
 
< 0.1%
47.9951293 1
 
< 0.1%
47.9950792 1
 
< 0.1%
47.994031 1
 
< 0.1%
47.9938994 1
 
< 0.1%
47.9930207 1
 
< 0.1%

MainBoxTemperature
Real number (ℝ)

Distinct49146
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.547603
Minimum0
Maximum54.25
Zeros228
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:41.034747image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile32.861408
Q139.151252
median39.547603
Q339.841104
95-th percentile46.921082
Maximum54.25
Range54.25
Interquartile range (IQR)0.68985192

Descriptive statistics

Standard deviation4.1709983
Coefficient of variation (CV)0.10546779
Kurtosis16.17153
Mean39.547603
Median Absolute Deviation (MAD)0.34827442
Skewness-1.5189205
Sum4669780.9
Variance17.397227
MonotonicityNot monotonic
2024-02-05T23:34:41.147685image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39.5476025 55573
47.1%
0 228
 
0.2%
39.375 46
 
< 0.1%
39.625 43
 
< 0.1%
39.5625 42
 
< 0.1%
39.3125 42
 
< 0.1%
40 41
 
< 0.1%
39.8125 39
 
< 0.1%
39.1875 39
 
< 0.1%
34.875 38
 
< 0.1%
Other values (49136) 61949
52.5%
ValueCountFrequency (%)
0 228
0.2%
14.16666667 1
 
< 0.1%
15.16666667 1
 
< 0.1%
15.22916667 1
 
< 0.1%
15.65 1
 
< 0.1%
15.8875 1
 
< 0.1%
15.9375 1
 
< 0.1%
16.28125 1
 
< 0.1%
16.34375 1
 
< 0.1%
16.46875 1
 
< 0.1%
ValueCountFrequency (%)
54.25 1
 
< 0.1%
54.2310007 1
 
< 0.1%
54.2301537 1
 
< 0.1%
54.18125 1
 
< 0.1%
54.175 1
 
< 0.1%
54.125 1
 
< 0.1%
54.1000004 1
 
< 0.1%
54.0657855 1
 
< 0.1%
54.002976 1
 
< 0.1%
54 4
< 0.1%

NacellePosition
Real number (ℝ)

Distinct6665
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean196.29054
Minimum0
Maximum357
Zeros242
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:41.254481image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile82.571429
Q1172
median196.29054
Q3196.29054
95-th percentile338
Maximum357
Range357
Interquartile range (IQR)24.290539

Descriptive statistics

Standard deviation69.08082
Coefficient of variation (CV)0.35193148
Kurtosis0.79017077
Mean196.29054
Median Absolute Deviation (MAD)18.290539
Skewness0.096969488
Sum23177987
Variance4772.1596
MonotonicityNot monotonic
2024-02-05T23:34:41.365921image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196.2905395 45802
38.8%
178 1343
 
1.1%
188 1289
 
1.1%
172 1249
 
1.1%
175 1201
 
1.0%
182 1184
 
1.0%
185 1089
 
0.9%
166 981
 
0.8%
169 938
 
0.8%
163 926
 
0.8%
Other values (6655) 62078
52.6%
ValueCountFrequency (%)
0 242
0.2%
0.5 1
 
< 0.1%
0.6 1
 
< 0.1%
1 3
 
< 0.1%
1.2 5
 
< 0.1%
1.285714286 1
 
< 0.1%
1.384615385 1
 
< 0.1%
1.5 46
 
< 0.1%
1.666666667 1
 
< 0.1%
1.714285714 1
 
< 0.1%
ValueCountFrequency (%)
357 254
0.2%
356.5 1
 
< 0.1%
356.4 1
 
< 0.1%
356.25 5
 
< 0.1%
356 5
 
< 0.1%
355.875 1
 
< 0.1%
355.8 3
 
< 0.1%
355.7142857 1
 
< 0.1%
355.6666667 1
 
< 0.1%
355.5 67
 
0.1%

ReactivePower
Real number (ℝ)

Distinct94041
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.133966
Minimum-203.18259
Maximum403.71362
Zeros642
Zeros (%)0.5%
Negative30592
Negative (%)25.9%
Memory size922.6 KiB
2024-02-05T23:34:41.475309image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum-203.18259
5-th percentile-11.237191
Q1-0.070556709
median78.8718
Q3109.12157
95-th percentile347.30663
Maximum403.71362
Range606.89621
Interquartile range (IQR)109.19213

Descriptive statistics

Standard deviation104.44382
Coefficient of variation (CV)1.1850575
Kurtosis0.65962742
Mean88.133966
Median Absolute Deviation (MAD)77.359656
Skewness1.2524131
Sum10406859
Variance10908.512
MonotonicityNot monotonic
2024-02-05T23:34:41.570132image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88.13396554 23332
 
19.8%
0 642
 
0.5%
347.36203 44
 
< 0.1%
-0.00027750563 8
 
< 0.1%
344.7782 5
 
< 0.1%
-9.131027 3
 
< 0.1%
350.4541 3
 
< 0.1%
-0.00022257098 3
 
< 0.1%
141.31088 3
 
< 0.1%
131.60054 2
 
< 0.1%
Other values (94031) 94035
79.6%
ValueCountFrequency (%)
-203.1825914 1
< 0.1%
-174.5518927 1
< 0.1%
-169.4634724 1
< 0.1%
-117.1323872 1
< 0.1%
-100.1500902 1
< 0.1%
-97.24960768 1
< 0.1%
-94.45873506 1
< 0.1%
-91.37651038 1
< 0.1%
-87.38554 1
< 0.1%
-83.13738821 1
< 0.1%
ValueCountFrequency (%)
403.71362 1
< 0.1%
368.53287 1
< 0.1%
363.3544544 1
< 0.1%
363.3376 1
< 0.1%
361.0306444 1
< 0.1%
359.637151 1
< 0.1%
359.364468 1
< 0.1%
358.0305657 1
< 0.1%
357.56088 1
< 0.1%
355.519659 1
< 0.1%

RotorRPM
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59255
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9074996
Minimum0
Maximum16.273495
Zeros2809
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:41.696041image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.75913661
Q19.8452371
median9.9074996
Q310.368189
95-th percentile15.692031
Maximum16.273495
Range16.273495
Interquartile range (IQR)0.52295207

Descriptive statistics

Standard deviation3.4225286
Coefficient of variation (CV)0.34544826
Kurtosis2.3156707
Mean9.9074996
Median Absolute Deviation (MAD)0.24482092
Skewness-1.1067378
Sum1169877.6
Variance11.713702
MonotonicityNot monotonic
2024-02-05T23:34:41.790581image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.907499647 55953
47.4%
0 2809
 
2.4%
11.564648 3
 
< 0.1%
15.64166 2
 
< 0.1%
9.24340475 2
 
< 0.1%
15.7423604 2
 
< 0.1%
9.2365331 2
 
< 0.1%
9.235785 2
 
< 0.1%
15.71970289 2
 
< 0.1%
9.2384215 2
 
< 0.1%
Other values (59245) 59301
50.2%
ValueCountFrequency (%)
0 2809
2.4%
0.0179586 1
 
< 0.1%
0.01817334783 1
 
< 0.1%
0.02904230133 1
 
< 0.1%
0.0326684 1
 
< 0.1%
0.03492094267 1
 
< 0.1%
0.03532348 1
 
< 0.1%
0.044406277 1
 
< 0.1%
0.0453589 1
 
< 0.1%
0.04704583333 1
 
< 0.1%
ValueCountFrequency (%)
16.273495 1
< 0.1%
16.070668 1
< 0.1%
16.001965 1
< 0.1%
15.994752 1
< 0.1%
15.993397 1
< 0.1%
15.979916 1
< 0.1%
15.94556267 1
< 0.1%
15.94000075 1
< 0.1%
15.91702483 1
< 0.1%
15.9161951 1
< 0.1%

TurbineStatus
Real number (ℝ)

Distinct354
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2280.4292
Minimum0
Maximum65746528
Zeros203
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:41.917573image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q12
median29
Q32280.4292
95-th percentile2280.4292
Maximum65746528
Range65746528
Interquartile range (IQR)2278.4292

Descriptive statistics

Standard deviation261744.49
Coefficient of variation (CV)114.77861
Kurtosis59310.826
Mean2280.4292
Median Absolute Deviation (MAD)28
Skewness243.39254
Sum2.6927308 × 108
Variance6.8510177 × 1010
MonotonicityNot monotonic
2024-02-05T23:34:42.026918image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2280.429214 55172
46.7%
2 55073
46.6%
1 2159
 
1.8%
3 1100
 
0.9%
16384 782
 
0.7%
512 286
 
0.2%
4 264
 
0.2%
8192 239
 
0.2%
1024 225
 
0.2%
0 203
 
0.2%
Other values (344) 2577
 
2.2%
ValueCountFrequency (%)
0 203
 
0.2%
1 2159
 
1.8%
2 55073
46.6%
3 1100
 
0.9%
4 264
 
0.2%
5 2
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
65746528 1
 
< 0.1%
61376732 1
 
< 0.1%
16384 782
0.7%
15604 1
 
< 0.1%
15522 1
 
< 0.1%
15474 2
 
< 0.1%
15124 1
 
< 0.1%
13927 2
 
< 0.1%
13312 1
 
< 0.1%
12544 1
 
< 0.1%

WindDirection
Real number (ℝ)

Distinct6665
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean196.29054
Minimum0
Maximum357
Zeros242
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:42.136517image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile82.571429
Q1172
median196.29054
Q3196.29054
95-th percentile338
Maximum357
Range357
Interquartile range (IQR)24.290539

Descriptive statistics

Standard deviation69.08082
Coefficient of variation (CV)0.35193148
Kurtosis0.79017077
Mean196.29054
Median Absolute Deviation (MAD)18.290539
Skewness0.096969488
Sum23177987
Variance4772.1596
MonotonicityNot monotonic
2024-02-05T23:34:42.248491image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196.2905395 45802
38.8%
178 1343
 
1.1%
188 1289
 
1.1%
172 1249
 
1.1%
175 1201
 
1.0%
182 1184
 
1.0%
185 1089
 
0.9%
166 981
 
0.8%
169 938
 
0.8%
163 926
 
0.8%
Other values (6655) 62078
52.6%
ValueCountFrequency (%)
0 242
0.2%
0.5 1
 
< 0.1%
0.6 1
 
< 0.1%
1 3
 
< 0.1%
1.2 5
 
< 0.1%
1.285714286 1
 
< 0.1%
1.384615385 1
 
< 0.1%
1.5 46
 
< 0.1%
1.666666667 1
 
< 0.1%
1.714285714 1
 
< 0.1%
ValueCountFrequency (%)
357 254
0.2%
356.5 1
 
< 0.1%
356.4 1
 
< 0.1%
356.25 5
 
< 0.1%
356 5
 
< 0.1%
355.875 1
 
< 0.1%
355.8 3
 
< 0.1%
355.7142857 1
 
< 0.1%
355.6666667 1
 
< 0.1%
355.5 67
 
0.1%

WindSpeed
Real number (ℝ)

Distinct94225
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8789597
Minimum0
Maximum22.970893
Zeros13
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size922.6 KiB
2024-02-05T23:34:42.341598image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.4793121
Q14.2833957
median5.8789597
Q36.9334885
95-th percentile10.222288
Maximum22.970893
Range22.970893
Interquartile range (IQR)2.6500929

Descriptive statistics

Standard deviation2.3442014
Coefficient of variation (CV)0.39874426
Kurtosis1.5363756
Mean5.8789597
Median Absolute Deviation (MAD)1.3613995
Skewness0.85580568
Sum694187.57
Variance5.4952803
MonotonicityNot monotonic
2024-02-05T23:34:42.457609image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.878959737 23485
 
19.9%
10.014299 47
 
< 0.1%
2.5037 33
 
< 0.1%
0 13
 
< 0.1%
2.7512999 12
 
< 0.1%
4.8122997 11
 
< 0.1%
4.4438 10
 
< 0.1%
5.0382 10
 
< 0.1%
4.6636996 9
 
< 0.1%
6.3863 8
 
< 0.1%
Other values (94215) 94442
80.0%
ValueCountFrequency (%)
0 13
< 0.1%
0.9 1
 
< 0.1%
0.957314967 1
 
< 0.1%
0.9623049455 1
 
< 0.1%
0.9802399545 1
 
< 0.1%
0.9999894142 1
 
< 0.1%
1.000244378 1
 
< 0.1%
1.00773494 1
 
< 0.1%
1.022844389 1
 
< 0.1%
1.028254936 1
 
< 0.1%
ValueCountFrequency (%)
22.97089311 1
< 0.1%
22.172939 1
< 0.1%
22.0232 1
< 0.1%
21.3920984 1
< 0.1%
20.17535792 1
< 0.1%
20.12793935 1
< 0.1%
19.9989395 1
< 0.1%
19.94138874 1
< 0.1%
19.55962193 1
< 0.1%
19.49505932 1
< 0.1%

Interactions

2024-02-05T23:34:36.148322image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:11.174770image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:12.960999image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:14.422024image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
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2024-02-05T23:34:30.550395image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:32.185664image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:34.082847image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:35.722199image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:37.514571image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:12.683625image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:14.151617image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:15.588487image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:17.018723image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:18.669150image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:20.201388image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:21.733715image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:23.567028image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:25.491863image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:27.183857image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:29.079887image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:30.650358image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:32.287334image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:34.189869image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:35.813930image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:37.632294image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:12.784002image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:14.249769image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:15.678873image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:17.113245image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:18.764206image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:20.296992image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:21.998978image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:23.701878image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:25.595942image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:27.284950image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:29.180991image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:30.748445image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:32.389848image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:34.283453image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:35.942043image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:37.749948image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:12.882438image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:14.344676image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:15.788372image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:17.353562image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:18.867924image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:20.396189image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:22.101044image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:23.887139image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:25.696610image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:27.384122image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:29.281892image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:30.850447image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:32.491091image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:34.364379image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2024-02-05T23:34:36.057868image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Correlations

2024-02-05T23:34:42.553367image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ActivePowerAmbientTemperatueBearingShaftTemperatureGearboxBearingTemperatureGearboxOilTemperatureGeneratorRPMGeneratorWinding1TemperatureGeneratorWinding2TemperatureHubTemperatureMainBoxTemperatureNacellePositionReactivePowerRotorRPMTurbineStatusWindDirectionWindSpeed
ActivePower1.000-0.0680.5330.6850.6420.7460.6980.6980.2390.0680.0140.7180.746-0.0070.0140.965
AmbientTemperatue-0.0681.0000.2100.0020.139-0.0390.0850.0850.4820.674-0.003-0.037-0.0390.028-0.003-0.096
BearingShaftTemperature0.5330.2101.0000.7340.6760.6410.7590.7580.7010.4250.1320.4610.641-0.0460.1320.521
GearboxBearingTemperature0.6850.0020.7341.0000.8320.8700.7750.7750.3870.1870.0860.6290.868-0.1110.0860.690
GearboxOilTemperature0.6420.1390.6760.8321.0000.7810.8040.8030.4270.2650.1440.5620.779-0.0200.1440.632
GeneratorRPM0.746-0.0390.6410.8700.7811.0000.8050.8060.2880.0800.0930.6810.994-0.1060.0930.754
GeneratorWinding1Temperature0.6980.0850.7590.7750.8040.8051.0000.9980.4190.2300.1550.5490.8060.1410.1550.677
GeneratorWinding2Temperature0.6980.0850.7580.7750.8030.8060.9981.0000.4190.2300.1550.5490.8060.1430.1550.677
HubTemperature0.2390.4820.7010.3870.4270.2880.4190.4191.0000.6850.1100.2040.288-0.1070.1100.224
MainBoxTemperature0.0680.6740.4250.1870.2650.0800.2300.2300.6851.0000.0310.0250.0820.0420.0310.052
NacellePosition0.014-0.0030.1320.0860.1440.0930.1550.1550.1100.0311.0000.1800.0940.0681.0000.009
ReactivePower0.718-0.0370.4610.6290.5620.6810.5490.5490.2040.0250.1801.0000.680-0.1850.1800.709
RotorRPM0.746-0.0390.6410.8680.7790.9940.8060.8060.2880.0820.0940.6801.000-0.1010.0940.754
TurbineStatus-0.0070.028-0.046-0.111-0.020-0.1060.1410.143-0.1070.0420.068-0.185-0.1011.0000.068-0.041
WindDirection0.014-0.0030.1320.0860.1440.0930.1550.1550.1100.0311.0000.1800.0940.0681.0000.009
WindSpeed0.965-0.0960.5210.6900.6320.7540.6770.6770.2240.0520.0090.7090.754-0.0410.0091.000

Missing values

2024-02-05T23:34:37.889060image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-05T23:34:38.347845image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampActivePowerAmbientTemperatueBearingShaftTemperatureGearboxBearingTemperatureGearboxOilTemperatureGeneratorRPMGeneratorWinding1TemperatureGeneratorWinding2TemperatureHubTemperatureMainBoxTemperatureNacellePositionReactivePowerRotorRPMTurbineStatusWindDirectionWindSpeed
02018-01-01 00:00:00+00:00-5.35772723.14872943.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.5476038.000000-9.9608309.90752280.4292148.0000002.279088
12018-01-01 00:10:00+00:00-5.82236023.03975443.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.547603300.428571-9.6284419.90752280.429214300.4285712.339343
22018-01-01 00:20:00+00:00-5.27940922.94870343.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.547603340.000000-9.4912359.90752280.429214340.0000002.455610
32018-01-01 00:30:00+00:00-4.64805422.96685143.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.547603345.000000-9.8561369.90752280.429214345.0000002.026754
42018-01-01 00:40:00+00:00-4.68463222.93652043.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.547603345.000000-9.7455939.90752280.429214345.0000001.831420
52018-01-01 00:50:00+00:00-4.75640822.92077743.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.547603345.000000-9.5699329.90752280.429214345.0000001.653846
62018-01-01 01:00:00+00:00-5.08978822.84909343.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.547603343.500000-9.6098459.90752280.429214343.5000001.633016
72018-01-01 01:10:00+00:00-5.11159622.69458343.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.547603324.500000-10.5933649.90752280.429214324.5000002.088558
82018-01-01 01:20:00+00:00-5.27793222.46729443.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.547603306.500000-9.5902019.90752280.429214306.5000002.090765
92018-01-01 01:30:00+00:00-4.43940222.59828943.01018964.2341757.5612171102.02626972.46040371.82665936.89797839.547603305.000000-9.1761959.90752280.429214305.0000001.952239
TimestampActivePowerAmbientTemperatueBearingShaftTemperatureGearboxBearingTemperatureGearboxOilTemperatureGeneratorRPMGeneratorWinding1TemperatureGeneratorWinding2TemperatureHubTemperatureMainBoxTemperatureNacellePositionReactivePowerRotorRPMTurbineStatusWindDirectionWindSpeed
1180702020-03-30 22:20:00+00:00145.02741527.58399846.36384762.24333256.6844901030.09826762.12310361.17403039.98246337.375000188.00000028.7097099.2347512.0188.0000003.954384
1180712020-03-30 22:30:00+00:00147.22369727.57723446.22317162.15461356.5140111030.34765661.60434660.65113939.73341037.210633188.00000029.9104689.2309502.0188.0000004.190217
1180722020-03-30 22:40:00+00:00117.70693927.50848946.08897561.78941456.2853591029.89133361.05847960.12313839.02452837.034593184.66666722.8465059.2336942.0184.6666673.949295
1180732020-03-30 22:50:00+00:0099.67023727.44042645.94107960.79723455.8865931029.65424060.29651159.35976239.03578436.846869178.00000020.1293949.2347922.0178.0000003.920965
1180742020-03-30 23:00:00+00:0090.33106527.58119345.81908460.27585155.5520221029.80543359.64873258.72939039.01039436.650659178.00000017.7928889.2352282.0178.0000003.612339
1180752020-03-30 23:10:00+00:0070.04446527.52374145.71112959.82116555.1937931029.87074459.06036758.14877739.00893136.476562178.00000013.7757859.2340042.0178.0000003.533445
1180762020-03-30 23:20:00+00:0040.83347427.60288245.59857359.14203854.7985451030.16047858.45200357.55036739.00675936.328125178.0000008.0889289.2293702.0178.0000003.261231
1180772020-03-30 23:30:00+00:0020.77779027.56092545.46204558.43943954.3804561030.13782258.03407157.09933539.00381536.131944178.0000004.3559789.2368022.0178.0000003.331839
1180782020-03-30 23:40:00+00:0062.09103927.81047245.34382758.20541354.0790141030.17817857.79538756.84723939.00381536.007805190.00000012.0180779.2373742.0190.0000003.284468
1180792020-03-30 23:50:00+00:0068.66442527.91582845.23161058.58171654.0805051029.83478957.69481356.74104039.00381535.914062203.00000014.4396699.2355322.0203.0000003.475205